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Digital Twin Trust & Value Assessment for Manufacturing

Measures internal stakeholder trust, perceived accuracy, and operational value of digital twins across manufacturing functions. Identifies adoption barriers and investment priorities to guide program improvements.

Sample questions

A preview of what’s in the template. Every question is editable before you launch.

22 questions · ~4 min
Q01
Long Text

Welcome, and thank you for participating in this survey about digital twins in our organization. The purpose is to understand how digital twins are used, trusted, and valued across different functions. Your participation is entirely voluntary and you may stop at any time. All responses are confidential and will be reported only in aggregate — there are no right or wrong answers. The survey takes approximately 5–7 minutes to complete.

Q02
Multiple Choice

What is your current level of involvement with our digital twins?

Q03
Multiple Choice

Which data sources are currently integrated into the digital twin(s) you use or support? (Select all that apply)

Q04
Long Text

Overall, how much do you trust the outputs from our digital twins today?

Q05
Multiple Choice

Which barriers most limit the adoption or impact of our digital twins today? (Select all that apply)

Q06
Long Text

What is one metric you would use to judge the digital twin's usefulness in your area?

Q07
Long Text

Where is your primary work location/region?

Q08
Long Text

Thank you for your time and insight! Your responses will help us prioritize improvements to our digital twin program.

Q09
Long Text

Which area best matches your current function?

Q10
Multiple Choice

How are the digital twin's outputs validated in your area? (Select all that apply)

Q11
Long Text

How useful is the digital twin for predicting or preventing production issues in your area?

Q12
Long Text

Rank the following areas by where investment would most improve digital twin trust and outcomes (most to least important).

Q13
AI Interview

Based on your responses in this survey, please share any additional thoughts or suggestions on how we can improve digital twin trust, usefulness, or adoption in your area.

Q14
Long Text

How many years have you worked in manufacturing or industrial operations?

Q15
Long Text

How accurately does the digital twin mirror current production conditions in your area?

Q16
Long Text

How useful is the digital twin for optimizing process parameters or throughput in your area?

Q17
Long Text

Are there any security or compliance risks related to our digital twins that you believe should be addressed? If so, please describe them briefly.

Q18
Multiple Choice

Which best describes your current role level?

Q19
Long Text

How useful is the digital twin for supporting planning, scheduling, or capacity decisions in your area?

Q20
Multiple Choice

What best describes your primary work environment?

Q21
Long Text

How useful is the digital twin for quality monitoring or root-cause analysis in your area?

Q22
Long Text

Rank the following factors by how much they increase your trust in a digital twin (most to least important).

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

  • AI-drafted copy

    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.